Senior AI Engineer

Core Responsibilities 

• Architect and deploy LLM-based solutions at scale (e.g., enterprise chat agents, document intelligence, domain-specific RAG) 
• Design agentic workflows using LangChain, A2A protocols, or custom-built orchestration layers 
• Develop and optimize prompt chaining logic, vector search strategies, and context management approaches (e.g., with MCP) 
• Integrate solutions with cloud-native platforms (Databricks, Azure Foundry), APIs, and enterprise data ecosystems 
• Lead technical design reviews, enforce best practices in code structure, testing, and observability 
• Conduct performance evaluations, token cost optimizations, and maintain reusability across solutions 
• Mentor Associate and AI Engineers through pair programming, design guidance, and code reviews 
• Stay ahead of emerging GenAI tooling and make recommendations for adoption in our stack 

Required Skills 

• 4–6+ years of experience in AI/ML engineering, with minimum 2 years working on GenAI/LLM use cases 
• Deep proficiency in Python, with fluency in libraries like OpenAI, Pydantic, Transformers, LangChain, FAISS, and Pandas 
• Demonstrated experience in building and deploying LLM-integrated applications using OpenAI or similar APIs 
• Strong knowledge of vector databases, prompt engineering strategies, and LLM context optimization 
• Hands-on with Azure cloud stack, GitHub/Azure DevOps CI/CD, and microservice/API design